Dynamic allocation of spectrum sensing resources in cognitive radio networks

ABSTRACT

A method, wireless controller, and information processing system are provided to dynamically allocate spectrum sensing resources. A first input ( 804 ) including available sensing session time for performing spectrum sensing with respect to one or more primary systems ( 102 ) is received. A second input ( 806 ) including a set of communication channels to be monitored in the spectrum sensing session is received. A third input ( 808 ) including detection constraints associated with a plurality of available sensing nodes ( 114 ) in a secondary network ( 104 ) for performing the spectrum sensing is received. Spectrum sensing resources are dynamically allocated ( 814 ) among a set of the plurality of available sensing nodes ( 114 ) based on the first ( 804 ), second ( 806 ), and third inputs ( 808 ).

FIELD OF THE INVENTION

The present invention generally relates to the field of wirelesscommunications, and more particularly relates to managing the allocationof spectrum sensing resources within a cognitive radio network.

BACKGROUND OF THE INVENTION

Wireless communication technology has evolved greatly over the recentyears. Recent studies have shown that the wireless spectrum in U.S. isunder-utilized, although most of the spectrum has been assigned tolicensees, or primary users. Therefore, spectrum sharing has beenproposed to alleviate the spectrum scarcity that prevents new wirelessservices being deployed. Cognitive radio is a promising technology thatcan allow secondary usage of spectrum without causing harmfulinterference to the primary systems. The secondary users, or cognitiveradios, are required to perform spectrum (channel) sensing beforeaccessing a channel that has been assigned to a licensed or primaryuser.

In order to reliably detect the primary signal, an individual radioneeds to have very high sensitivity to offset the fading and shadowingconditions of a radio channel. To overcome the difficulties that anindividual radio experiences in determining channel occupancy,cooperative sensing is proposed to improve the performance of detection.For a more detailed discussion on cooperative sensing see S. M. Mishra,A. Sahai, and R. W. Broderson, “Cooperative sensing among cognitiveradios”, Proc. IEEE ICC 2006, Istanbul, Turkey, June, 2006 and A.Gashemi and E. Sousa, “Impact of user collaboration on the performanceof sensing-based opportunistic spectrum access”, Proc. IEEE VTC 2006,pp. 1-6, Fall 2006, both of which are hereby incorporated by referencein their entireties.

In cooperative sensing, the final decision is made by a central nodeusing the sensing data collected by the distributed radios. Althoughthere have been many publications related to cooperative sensing, thereis no systematic method on how to dynamically allocate the spectrumsensing resources: such as the sensing time for each candidate channel;the number of radios need to be included in collaborative sensing, andother spectrum sensing resources.

Therefore a need exists to overcome the problems with the prior art asdiscussed above.

SUMMARY OF THE INVENTION

A method with a wireless communication controller for dynamicallyallocating spectrum sensing resources in an opportunistic spectrumaccess wireless communication system is disclosed. The method includesreceiving a first input comprising available sensing session time forperforming spectrum sensing with respect to one or more primary systems.A second input comprising a set of communication channels to bemonitored during spectrum sensing is received. A third input comprisingdetection constraints associated with a plurality of available sensingnodes in a secondary network for performing the spectrum sensing isreceived. Spectrum sensing resources are dynamically allocated among aset of the plurality of available sensing nodes based on the first,second, and third input.

In another embodiment, a wireless communication controller is disclosed.The wireless communication controller includes a cognitive engineadapted to receive a first input comprising available sensing sessiontime for performing spectrum sensing with respect to one or more primarysystems. A second input comprising a set of communication channels to bemonitored during spectrum sensing is received. A third input comprisingdetection constraints associated with a plurality of available sensingnodes in a secondary network for performing the spectrum sensing isreceived. The wireless communication controller also includes a dynamicresource allocator communicatively coupled to the cognitive engine. Thedynamic resource allocator is adapted to dynamically allocating spectrumsensing resources among a set of the plurality of available sensingnodes based on the first, second, and third input.

In yet a further embodiment an information processing system isdisclosed. The information processing system includes a memory and aprocessor communicatively coupled to the memory. A wirelesscommunication controller is communicatively coupled to the memory andthe processor. The wireless communication controller includes acognitive engine adapted to receive a first input comprising availablesensing session time for performing spectrum sensing with respect to ahost network. A second input comprising a set of communication channelsto be monitored during spectrum sensing is received. A third inputcomprising detection constraints associated with a plurality ofavailable sensing nodes in a secondary network for performing thespectrum sensing is received. The wireless communication controller alsoincludes a dynamic resource allocator communicatively coupled to thecognitive engine. The dynamic resource allocator is adapted todynamically allocate spectrum sensing resources among a set of theplurality of available sensing nodes based on the first, second, andthird input.

An advantage of various embodiments of the present invention is thatspectrum sensing resources for cognitive radio applications aredynamically allocated to account for continuously changing radio andnetwork environments. In particular, various embodiments of the presentinvention manage the dynamics of a Cognitive Radio (“CR”) network thatneed to satisfy both network throughput requirements and spectrumsensing requirements.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying figures where like reference numerals refer toidentical or functionally similar elements throughout the separateviews, and which together with the detailed description below areincorporated in and form part of the specification, serve to furtherillustrate various embodiments and to explain various principles andadvantages all in accordance with the present invention.

FIG. 1 is block diagram illustrating a wireless communication systemaccording to one embodiment of the present invention;

FIG. 2 is a block diagram illustrating one example of a super-frameaccording to one embodiment of the present invention;

FIG. 3 is a detailed view of an information processing system configuredto perform dynamic allocation of spectrum sensing resources according toone embodiment of the present invention;

FIG. 4 is a timing diagram illustrating resource allocation over timeaccording to one embodiment of the present invention;

FIG. 5 is s block diagram showing partitioning of a sensing frame withina super frame according to one embodiment of the present invention;

FIG. 6 is a block diagram illustrating a detailed view of a wirelessdevice according to one embodiment of the present invention;

FIG. 7 is a block diagram illustrating a detailed view of an informationprocessing system according to one embodiment of the present invention;and

FIG. 8 is an operational flow diagram illustrating a process ofdynamically allocating spectrum sensing resources according to oneembodiment of the present invention.

DETAILED DESCRIPTION

As required, detailed embodiments of the present invention are disclosedherein; however, it is to be understood that the disclosed embodimentsare merely examples of the invention, which can be embodied in variousforms. Therefore, specific structural and functional details disclosedherein are not to be interpreted as limiting, but merely as a basis forthe claims and as a representative basis for teaching one skilled in theart to variously employ the present invention in virtually anyappropriately detailed structure. Further, the terms and phrases usedherein are not intended to be limiting; but rather, to provide anunderstandable description of the invention.

The terms “a” or “an”, as used herein, are defined as one or more thanone. The term plurality, as used herein, is defined as two or more thantwo. The term another, as used herein, is defined as at least a secondor more. The terms including and/or having, as used herein, are definedas comprising (i.e., open language). The term coupled, as used herein,is defined as connected, although not necessarily directly, and notnecessarily mechanically.

The term “wireless device” is intended to broadly cover many differenttypes of devices that can wirelessly receive signals, and optionally canwirelessly transmit signals, and may also operate in a wirelesscommunication system. For example, and not for any limitation, awireless communication device can include (but is not limited to) anyone or a combination of the following: a two-way radio, a cellulartelephone, a mobile phone, a smartphone, a two-way pager, a wirelessmessaging device, a laptop/computer, automotive gateway, or aresidential gateway.

Wireless Communication System

According to one embodiment of the present invention as shown in FIG. 1one example of a wireless communication system 100 is illustrated. FIG.1 shows a plurality of networks 102, 104. Although only two networks102, 104 are shown, the wireless communication system 100 can compriseadditional networks. In one embodiment, one of the networks 102 is ahost/primary network and one or more of the additional networks aresecondary networks 104. In one embodiment, a host/primary network can bean underlay network and a secondary network can be an overlay network.The host/primary network 102 is assigned RF spectrum that is dividedinto channels that can potentially be used by the secondary network(s)104. Throughout this discussion the terms “host” and “primary” thatrefer to, for example, host/primary network 102, are usedinterchangeably. The type of wireless communication system that allowsfor a secondary network to utilize the RF spectrum of a host/primarynetwork is commonly referred to as Cognitive Radio (“CR”) system.

Each of the wireless communication networks 102, 104 can include one ormore communication networks 106, 108 such as a circuit service networkand/or a packet data network. The communication networks 106, 108 caneither be wired or wireless. The wireless communications standard of thenetworks 102, 104 coupling bases stations 110, 112 to mobiles 114 to 122can comprise Code Division Multiple Access (“CDMA”), Time DivisionMultiple Access (“TDMA”), Global System for Mobile Communications(“GSM”), General Packet Radio Service (“GPRS”), Frequency DivisionMultiple Access (“FDMA”), other IEEE 802.16 standards, OrthogonalFrequency Division Multiplexing (“OFDM”), Orthogonal Frequency DivisionMultiple Access (“OFDMA”), Wireless LAN (“WLAN”), WiMAX, or the like.The wireless communications networks 102, 104 are able to be an IP orSIP based connectivity network, which provides data connections at muchhigher transfer rates then a traditional circuit services network. Thesenetworks are able to comprise an Evolution Data Only (“EV-DO”) network,a General Packet Radio Service (“GPRS”) network, a Universal MobileTelecommunications System (“UMTS”) network, an 802.11 network, an 802.16(WiMAX) network, Ethernet connectivity, dial-up modem connectivity, orthe like.

A circuit services network is able to provide, among other things, voiceservices to the wireless devices 114 to 122 communicatively coupled toone or both of networks 102, 104. Other applicable communicationsstandards include those used for Public Safety Communication Networksincluding TErrestrial TRunked rAdio (“TETRA”) and P25 Trunking. Itshould be noted that these network technologies are only used as anillustrative example and do not limit further embodiments of the presentinvention. Each of the wireless communication networks 102, 104 includesa plurality of base stations 110, 112. Each of the base stations 110,112 is communicatively coupled to an information processing system 126,128 such as a site controller 126, 128.

As discussed above, the wireless communication system 100, in oneembodiment, is a CR system. In a cognitive radio (CR) system of the typeconsidered for use by IEEE 802.22, a cognitive secondary radio systemutilizes spectrum assigned to a primary system using an opportunisticapproach. With this approach, the secondary radio system shares thespectrum with primary incumbents as well as those operating underauthorization on a secondary basis. Under these conditions, it isimperative that any user in the cognitive radio system not interferewith primary users. Some types of cognitive radio systems (e.g., IEEE802.22) require that devices sense the channel to detect a licensed,primary user. The devices are allowed to transmit if their transmissionswill not interfere with any primary user. This is generally accomplishedby the secondary user determining the signal strength of the primaryusers, and if the signal of any primary user is above a predeterminedthreshold, the cognitive radio device determines that its transmissionswould cause interference to the primary user, and so inhibitstransmission.

In the example of FIG. 1, the secondary network 104 includes a pluralityof sensing nodes that perform spectrum sensing with respect to thehost/primary network 102. For example, one or more of the wirelessdevices 114, 116, 118 within the secondary network 104 can performspectrum sensing. Therefore, one or more of the secondary networkwireless devices 114, 116, 118 includes a spectrum sensing engine 130,132, 134 for performing the spectrum sensing. The spectrum sensingengines 130, 132, 134 are discussed in greater detail below. It shouldbe noted that one or more of the base stations 112 within the secondarynetwork 104 can also perform spectrum sensing with respect to thehost/primary network 102. Therefore, the site controller 128, in oneembodiment, also includes a spectrum sensor 136 as well.

The wireless communication system 100 also includes one or moreinformation processing systems 136 such as a network controller oraccess point that controls and manages the networks 102, 104.Additionally, the wireless communication system 100 includes one or morecognitive radio information servers 148 that can facilitate thedeployment of the CR networks. In one embodiment, the cognitive radioinformation server 148 includes a primary network database 149 andcognitive radio policies 151.

As discussed above, CR systems in general do not dynamically allocatethe spectrum sensing resources to account for the changing environment.Therefore, to overcome this problem the information processing system138, in one embodiment includes a cognitive engine 140 with a dynamicresource allocator 142 for dynamically allocating spectrum sensingresources. The information processing system 138, in one embodiment,accepts as one or more inputs information associated with primarynetworks (i.e., information within the primary network database 149)and/or policies 151 regarding cognitive radio network, from thecognitive radio information server 148. Stated differently, thecognitive engine 140 of the information processing system 138 managesthe dynamic behavior of cooperative spectrum sensing in cognitive radionetworks by dynamically allocating the spectrum sensing resourcesaccording to the current network throughput requirement and CR policyrequirements. It should be noted that the information processing system138 can also perform spectrum sensing as well. Spectrum sensingresources can include but are not limited to spectrum sensing time foreach candidate channel; the number of radios assigned to performcollaborative sensing per channel; the collaborative sensing method; andthe protocol to collect sensing results from different wireless devices.The dynamic management of spectrum sensing resources is discussed ingreater detail below.

It should be noted that the present invention is not limited to having acentral location comprising the cognitive engine 140 and dynamicresource locator 142. For example, a distributed system can be usedcomprising various nodes within the wireless communication system. Oneor more of the nodes can include a cognitive engine 140 and dynamicresource locator 142. Each of the nodes can communicate information tothe other nodes to be used by each cognitive engine 140 and dynamicresource locator 142 so spectrum sensing resources can be dynamicallyallocated.

Dynamic Spectrum Sensing Resource Allocation and Management

At the outset, distributed sensing was motivated for the most part bymilitary surveillance applications. For example, in radar detection, agroup of sensors work to make a multi-sensor decision regarding thepresence or absence of a target based on radar return. In many cases,complete observations are sent to the fusion center and where optimaldetection algorithms are employed. Research in this field then evolvedto consider decentralized processing. A review of two influential surveypapers (Vishwanthan R. and Varshney P., “Distributed Detection withMultiple Sensors: Part I—Fundamentals”, Proc. of the IEEE, pp. 54-63,vol. 85, No. 1 Jan. 1997 and Blum R., Kassam S. and Poor V.,“Distributed Detection with Multiple Sensors: Part II-Advanced Topics”,Proc. of the IEEE, pp. 64-78, vol. 85, No. 1 Jan. 1997, which are herebyincorporated by reference in their entireties), which summed up resultsfrom 61 and 71 papers in the field respectively, indicates that much ofthe publicly available literature in the field focuses on developingcomputationally efficient detection algorithms at the sensors and fusioncenter.

A related problem, data aggregation, has been studied under the wirelesssensor network (“WSN”) topic (See Vishwanthan R. and Varshney P.,“Distributed Detection with Multiple Sensors: Part I—Fundamentals”,Proc. of the IEEE, pp. 54-63, vol. 85, No. 1 Jan. 1997 and Blum R.,Kassam S. and Poor V., “Distributed Detection with Multiple Sensors:Part II-Advanced Topics”, Proc. of the IEEE, pp. 64-78, vol. 85, No. 1Jan. 1997.). In WSN, the sensing nodes are energy constrained and thenetwork structure is also highly dynamic, therefore an optimal dataaggregation method is needed to achieve energy efficiency. These resultscould be applied to the cooperative spectrum sensing, in particular, thedesign of the cooperation protocol that collects sensing results fromindividual radios. However, cooperative spectrum sensing differs greatlyfrom WSN because in CR applications, spectrum sensing is an auxiliaryfunctionality, whereas the main goal is to maximize CR networkthroughput while limiting interference to the primary users.

Therefore, spectrum sensing needs to be considered together with thenetwork throughput requirement. Accordingly, various embodiments of thepresent invention, for example, implement a cognitive engine 140 with adynamic resource allocator 142 that determines when to perform spectrumsensing and how long the devices in the network must be quiet in orderto perform spectrum sensing. Then the cognition engine 140, determinesthe optimal way to perform spectrum sensing by dynamically allocatingsensing resources appropriately. The allocation of sensing resourcesincludes but is certainly not limited to the data aggregation method.The interaction between application/network QoS requirement and spectrumsensing is not considered in the data aggregation for WSN.

In one embodiment, the CR network such as the wireless communicationsystem 100 of FIG. 1 operates on a super-frame by super-frame basis.FIG. 2 shows one example of a sequence of super-frames 202, 204. Thereare two types of frames in each super-frame: data communication frames206 and spectrum sensing frames 208. A time division protocol, in oneembodiment, is used to divide the super-frame 202 into the two smallerframes 206, 208. The duration of the spectrum sensing frame 208 and thefrequency of sensing frame 208 can vary in time in order to satisfy thenetwork throughput requirements. The network throughput requirements canvary based on the requirements of different applications.

In one embodiment, the cognitive engine 140 at the informationprocessing system 138 dynamically changes the frame structure of thesuper-frame 202, 204 to allow for dynamic spectrum sensing. Based on anapplication's (306 in FIG. 3) network throughput requirement and thepolicy requirement (310 of FIG. 3) of a CR network such as the wirelesscommunication system 100, the cognitive engine 140 of the informationprocessing system 138 dynamically determines the following two keyparameters for spectrum sensing: 1.) when spectrum sensing should beperformed (e.g., the length of the current data transmission framedecides the starting time of next spectrum sensing frame) and 2.) thelength of the spectrum sensing frame (e.g., the longer the spectrumsensing frame, the lower the network throughput).

As far as the spectrum sensing is concerned, the first parameter onlycontrols the synchronization of spectrum sensing, since a quiet periodis likely needed. The second parameter is the key constraint for thepurpose of resource allocation of spectrum sensing. The cognitive engine140 (via the dynamic resource allocator 142) of the informationprocessing system 138 also considers the following parameters whendynamically allocating spectrum resources: 1.) if a list of candidatechannels that need to be sensed exists, the dynamic resource allocator142 determines how many of the channels in the list are to be sensed;2.) the dynamic resource allocator 142 determines how long should thesensing time for each channel be, since the total sensing time ispredetermined; and 3.) the dynamic resource allocator 142 determines howmany radios should participate in the sensing for a particular channel,if cooperative sensing is used.

The information processing system 138, in one embodiment, via thecognitive engine 140 and the dynamic resource allocator 142 performs asystematic method to address these issues by casting the administrationof cooperative spectrum sensing as a dynamic resource allocationproblem. The information processing system 138 is shown in greaterdetail with respect to FIG. 3. In particular, FIG. 3 shows the systemarchitecture of the information processing system 138 for dynamicallyallocating resources for spectrum sensing.

The functional components inside a CR radio can be divided intoCognition Engine (“CE”) related components, as shown by the first dashedbox 302 and non-CE related components, as shown by the second dashed box304. As discussed above, the information processing system 138 includesa cognitive engine 140 including a dynamic resource allocator 142 formanaging spectrum sensing and performing dynamic allocation of thespectrum sensing resources (e.g., spectrum sensing time for eachcandidate channel; the number of radios assigned to performcollaborative sensing per channel; the collaborative sensing method; andthe protocol to collect sensing results from different wirelessdevices).

FIG. 3 also shows various components within the information processingsystem 138 that act as inputs for the cognitive engine 140 and thedynamic resource allocator 142. For example, FIG. 3 shows one or moreapplications 306 and a protocol stack 308 at the non-CE related portion304 of the information processing system 138. FIG. 3 also shows a policyengine 310, a location database 312, and a spectrum sensing resultsmemory 314 at the CE-related side 302 of the information processingsystem 138. The application(s) 306, in one embodiment, is a networkthroughput statistics application that can dynamically determine thelength of the sensing frame 202 for the next super-frame 204. Forexample, if the application 306 determines that a heavy load is expectedon the network 102, the application 306 can stipulate a shortenedsensing period (i.e., longer data communication period) and relay thisto the cognitive engine 140. This sensing frame can vary in length in aframe-by-frame basis, but not necessarily. The application protocolstack 308, in one embodiment, derives certain network statistics for thecognitive engine 140. For example, the application protocol stack 308can determine the communication cost related to cooperative spectrumsensing.

The policy engine 310 includes various policies such as those thatdetermine how primary users on the host/primary network 102 are to beprotected. Stated differently, the policy engine 310 can includepolicies that help mitigate interference between secondary wirelessdevices 114, 116, 118 and the primary wireless devices 120, 122. Thepolicy engine 310 communicates with the cognitive radio informationserver 148 to update policies 151 periodically or when the AP locationis changed. The policy engine 310 allows the cognitive engine 140 toderive the current requirement on spectrum sensing such as theprobability of detection for a particular primary system and use this asone input. The location database 312 includes location dependentinformation such as the candidate channel list for the specific locationwhere the CR network such as the wireless communication system 100 islocated. The spectrum sensing results memory 314 includes spectrumsensing results received from the spectrum sensing nodes such as thebase stations 110, 112, the wireless devices 114, 116, 118, and/or theinformation processing system 138 itself. These spectrum sensing resultsare used by the cognitive engine 140 and the dynamic resource allocator142 to determine future resource allocation for spectrum sensing.

The cognitive engine takes the inputs received from the application(s)306, application protocol stack 308, policy engine 310, locationdatabase 312, and the spectrum sensing results memory 314, and based onthese inputs the dynamic resource allocator generates a resourceallocation table 316 for cooperative spectrum sensing. This resourceallocation table 316 is then transmitted to the sensing nodes for use bythe spectrum sensing engines as shown by box 318. Because the inputsreceived by the cognitive engine 140 and the dynamic resource allocator142 are continually changing, the resource allocation table 316 isperiodically updated. For example, the dynamic resource allocator 142can update the resource allocation table 316 after every sensing frame208, every super-frame 202, or at any other given point in time.

FIG. 4 shows one example of the resource allocation table 316. Inparticular, the resource allocation table 316 of FIG. 4 includes anentry for a particular sensing node such as sensing node R1, sensingnode R2, sensing node R3, sensing node R4, and sensing node R5. Theexample of FIG. 4 shows that 5 sensing nodes in the secondary network104 can be used to perform cooperative spectrum sensing for 3 channelsselected for the region where the secondary network 104 is deployed. Itshould be noted that the dynamic resource allocator 142 is not limitedto using all available sensing nodes within the network 104. Forexample, if only five sensing nodes are available then the dynamicresource allocation can choose a number of sensing nodes that is lessthan five. The spectrum sensing frame 208 is further divided intosub-frames 402, 404, where in each sub-frame 402, 404 a sensing nodeperforms sensing on only one particular channel. In the first sub-frame402 inside the spectrum sensing frame 208, 3 sensing nodes, sensing nodeR1, sensing node R2, and sensing node R3, are used to sense channel 1,and 2 sensing nodes, sensing node R4 and sensing node R5, are used tosense channel 2.

In the second sub-frame 404 in the spectrum sensing frame 208, all 5sensing nodes to sense channel 3. As an example, FIG. 4 shows that afirst entry 406 specifies that: from time 0 to time T1, sensing node R1is to participate in sensing channel 1 and from time T1 to time T2 thesensing node R1 is to participate in sensing channel 3. As can be seen,the dynamic resource allocator 142 is able to dynamically allocate thesensing resources, which could vary between frames.

Although in the example of FIG. 4 a sensing node is assumed to onlyperform sensing on one particular channel, the present invention is notlimited to such an implementation. For example, if the RF front end haswider bandwidth than that of one channel, a sensing node can thenperform sensing on more than one channel in each sub-frame.

Current CR systems generally use a fixed number of sensing nodes, whichis usually all of the available sensing nodes that are available toperform sensing. These current CR systems also use one fixed sensingtime or a set of predetermined sensing periods. Using all availablesensing nodes is problematic because bandwidth and other criticalresources become constrained. Using a fixed sensing period does not takethe changing environment into account and can also place constraints onsystem resources. As can be seen from FIG. 4 above, the dynamic resourceallocator 142 takes into account many factors such as spectrum sensingrequirements and network throughput requirements to determine anoptimized number of sensing nodes to select for perform sensing. Thedynamic resource allocator 142 also dynamically determines the amount oftime each selected sensing node is to perform the sensing operation on aparticular channel. Stated differently (and as can be seen from FIG. 4),the dynamic resource allocator 142 can dynamically set a sensing period,dynamically select a number of sensing resources to perform sensingwithin that sensing period, dynamically select the channels to be sensedwithin that sensing period, and divide the sensing period intosub-periods that can be used further sensing of different channels (e.g.sensing node R1 is to perform sensing from time T0 to T1 fro channel 1and from T1 to T2 for channel 3).

A possible implementation goal of the resource allocation performed bythe dynamic resource allocator 142 is to maximize the combinedachievable network throughput across all candidate channels. In thisembodiment, it is assumed that there are k channels in the candidatechannel list (which can reside in the location database 312). Normally,the channels in the channel list are identified to be vacant based onprevious sensing results. However, these channels might have differentcapacities due to the different maximum transmit powers and differentenvironmental noise levels. Therefore, C_(j) is defined as theachievable network throughput (NT) if a sensing node uses a particularchannel j, given by,

NT_(j)=(1−P _(fa,j))C _(j).  (1)

The achievable throughput is scaled by the probability of correctlyidentifying the availability of a particular channel, where P_(fa,j) isthe probability of false alarms for that particular channel. So thespectrum sensing resources are allocated by the dynamic resourceallocator 142, in one embodiment, to maximize the total achievablenetwork throughput, given by,

$\begin{matrix}{{NT} = {\sum\limits_{j = 1}^{k}{( {1 - P_{{fa},j}} ){C_{j}.}}}} & (2)\end{matrix}$

The maximization is constrained by the limited sensing resources,constraints include, but are not limited to: 1.) the probability ofdetection for each channel which is to be no less than what is specifiedby the policy engine 310; 2.) the total sensing time across all thechannels which combined must be smaller or equal to T, which isdetermined by application requirement (e.g., determined by theapplication 306) (this T parameter can vary from time to time, thereforerequires the allocation to be updated frame-by-frame); and 3.) the totalnumber of radios is limited to N, which is the number of radios in thecurrent CR network such as the wireless system 100 of FIG. 1.

The following is a simplified example that demonstrates the need for theoptimal dynamic allocation of spectrum sensing resources performed bythe dynamic resource allocator 142. In this example, it is assumed thatin each sensing super-frame 502 (FIG. 5), the sensing function is onlyperformed on one channel. It is also assumed that for this particularchannel, the directive from the policy engine 310 is to achieve adesired level of spectrum sharing. Namely, the probability of falsealarm is to be less than a certain percentage when there is no primaryuser present. The sensing frame 502 comprises a channel sensingsub-frame 504 and a sensing results reporting sub-frame 506. In thechannel sensing sub-frame 504, all sensing nodes perform sensing on thechannel condition.

All the sensing nodes remain quiet during this sub-frame 504, acting assensing receiver only. In the sensing results collection sub-frame 506,the information processing system 138 collects the sensing results fromthe sensing nodes that participated in the cooperative sensing. Thespectrum sensing resources, in this example, therefore include: thenumber of radios that can participate in the cooperative spectrumsensing and the length of the channel sensing frame and the channelcollection frame. The optimization objective, in this example, is tomaximize the potential network throughput (NT) of the primary user ifthe primary user is present, i.e.,

NT_(p)=(1−P _(md)·) C _(p),  (3)

where C_(p) is the channel capacity of the primary user, and P_(md) isthe probability of misdetection from spectrum sensing.

Because the sensing nodes cannot change anything about the primarysystem's channel capacity, equation (3) is simply reduced to minimizethe probability of misdetection, or maximize the probability ofdetection, with respect to the primary user. The current example assumesthat the following parameters are known or already determined based onpolicy from the policy engine 310 and the application requirementdetermined by the application 306: 1.) the overall network levelprobability of false alarm: Q_(fa); 2.) the total sensing period: T(although the time T might vary adaptively based on network load andenvironment dynamics, it should be determined before scheduling the nextspectrum sensing operation); and 3.) sensing results transmit time perradio per channel: C (there is a communication cost associated with thesensing results collection, no matter hard decision combing (one bit) orsoft combining (quantized measurement data)). Based on theseassumptions, the general cooperative sensing optimization problem isformulated as: Given total sensing period T, where T=T_(m)+(N−1)*C,choose N, such that the spectrum sensing performance is optimal in termsof equation (3).

The following is a cooperative sensing example where individual sensingnodes perform power detection based sensing. Based on a Constant FalseAlarm Rate (“CFAR”) assumption, the problem becomes how to find thevalue of N such that the network throughput of equation (1) ismaximized. It can be seen that maximizing equation (1) is equivalent tominimizing:

w=ln((1−p _(d))^(N))=N ln(1−p _(d))  (4)

In order to find the N so that equation (3) can be minimized, thederivative with respect to N is taken and is set to 0,

$\begin{matrix}{\frac{w}{N} = {{{\ln ( {1 - p_{d}} )} - {\frac{N}{1 - P_{d}} \cdot \frac{P_{d}}{N}}} = 0}} & (5)\end{matrix}$

In both equation (4) and equation (5), Pd is the radio level probabilityof detection, which is a function of N. M is defined to be the productof observation time and signal bandwidth. This example further assumesthat all the time measurements in the following derivation arenormalized with respect to the reciprocal of signal bandwidth. In otherwords, when the total sensing period is referred to as T, this meansthat the product of the sensing period and bandwidth is T. For the sakeof completeness, the derivation of Pd is repeated as follows. When thetime-bandwidth product M is large enough, the output of power detector(Y) can be approximated by a Gaussian probability distribution function(pdf) as

$\begin{matrix}{Y \sim {N( {\sigma_{x}^{2},\frac{2\sigma_{x}^{4}}{M}} )}} & (6)\end{matrix}$

where σ_(x) ² is the variance of the input signal x[n], which is assumedto be zero mean and Gaussian distributed.

The spectrum sensing example was considered based on CFAR detection andthe collaborative sensing using OR decision combining. Given apre-determined network level false alarm probability Q_(fa), based onequation (2), the false alarm probability of a radio is derived by

P _(fa)=1−(1−Q _(fa))^(1/N)  (7)

Therefore the threshold used in the power detector can be derived by

$\begin{matrix}{\gamma = {\sigma_{x}^{2}( {1 + \frac{Q^{- 1}( P_{fa} )}{\sqrt{M/2}}} )}} & (8)\end{matrix}$

Then the detection probability at each radio is determined by the powerof the signal, or the signal to noise ratio (“SNR”), i.e.,

$\begin{matrix}{P_{d} = {{Q\lbrack \frac{{Q^{- 1}( P_{fa} )} - {\sqrt{M/2}{SNR}}}{1 + {SNR}} \rbrack} \equiv {Q(u)}}} & (9)\end{matrix}$

where Q is a complimentary error function. From equation (5), thederivative of Pd with respect to N is calculated using equation (9),

$\begin{matrix}{\frac{P_{d}}{N} = {{\frac{Q}{u} \cdot \frac{u}{N}} \equiv {Y \cdot Z}}} & (10)\end{matrix}$

After an algebraic calculation, Y and Z can be determined usingequations (11) and (12), respectively.

$\begin{matrix}{Y = {{- \frac{1}{\sqrt{2\pi}}}^{{- u^{2}}/2}}} & (11) \\{Z = {\frac{1}{1 + {SNR}}\{ {\frac{\frac{\sqrt{2\pi}{{\exp ( {( {Q^{- 1}( P_{fa} )} )^{2}/2} )} \cdot}}{( {1 - Q_{fa}} )^{\frac{1}{N}}{\ln ( {1 - Q_{fa}} )}}}{N^{2}} + \frac{{SNR} \cdot C}{\sqrt{8M}}} \}}} & (12)\end{matrix}$

In equation (12), C is the communication time for each radio to send itssensing result to the controller. The total sensing period T, the powerdetection dwell time M, and the communication cost C satisfies

T=M+(N−1)·C  (13)

Combining equations (10), (11), and (12), and then plugging the resultinto equation (5) yields:

$\begin{matrix}{\frac{w}{N} = {{{\ln ( {1 - P_{d}} )} - \frac{N \cdot Y \cdot Z}{1 - P_{d}}} = 0}} & (14)\end{matrix}$

By solving equation (14), the optimal number of sensing nodes N can befound, such that the collaborative spectrum sensing can achieve maximalprobability of detection on the primary user, given the pre-determinedtotal sensing period, the communication time of sensing result perradio, and the expected signal power of primary user (or SNR).

As can be seen from the above discussion, various embodiments of thepresent invention can dynamically allocate spectrum sensing resources(such as the spectrum sensing time for each candidate channel; thenumber of radios assigned to perform collaborative sensing per channel;the collaborative sensing method; and the protocol to collect sensingresults from different MS. When the sensing super-frame starts, the CRnetwork will perform collaborative spectrum sensing based on the optimalresource allocation) for cognitive radio applications. The variousembodiments manage the dynamics of a CR network that needs to satisfyboth network throughput requirement and spectrum sensing requirements.

Sensing nodes such as the base stations, wireless devices, and/or thenetwork controller/access point perform spectrum sensing. A timedivision protocol is used to divide the time into two types ofsuper-frames: a data communication super-frame and a spectrum sensingsuper-frame. The spectrum sensing related tasks are limited to thededicated spectrum-sensing super-frame. These tasks include spectrumsensing (measurement collection and processing) and reporting of thesensing results to the information processing system 138 whencollaborative sensing is used. Based on the QoS requirement of theapplication and the CR policy requirement, the cognitive engine 140determines the time duration to perform spectrum sensing and theduration of the spectrum sensing super-frame. In addition to the policyengine, the geolocation database 312 inside the information processingsystem 138 determines the number of candidate channels for spectrumsensing, and the sensing requirements on these channels, such asprobabilities of detection and false alarm. These dynamic parameters arethen sent to the cognition engine 140, where the dynamic resourceallocator 142 performs optimal spectrum sensing resource allocation in adynamic fashion.

Exemplary Wireless Device

FIG. 6 is a block diagram illustrating a detailed view of a wirelessdevice 114 according to one embodiment of the present invention. It isassumed that the reader is familiar with wireless communication devices.To simplify the present description, only that portion of a wirelesscommunication device that is relevant to the present invention isdiscussed. The wireless device 114 operates under the control of adevice controller/processor 602, that controls the sending and receivingof wireless communication signals. In receive mode, the devicecontroller 602 electrically couples an antenna 604 through atransmit/receive switch 606 to a receiver 608. The receiver 608 decodesthe received signals and provides those decoded signals to the devicecontroller 602.

In transmit mode, the device controller 602 electrically couples theantenna 604, through the transmit/receive switch 606, to a transmitter610. It should be noted that in one embodiment, the receiver 608 and thetransmitter 610 are a dual mode receiver and a dual mode transmitter forreceiving/transmitting over various access networks providing differentair interface types. In another embodiment a separate receiver andtransmitter is used for each of type of air interface. A memory 612includes, among other things, the spectrum sensing engine 130, which hasbeen discussed above. The wireless device 114, also includesnon-volatile storage memory 614 for storing, for example, an applicationwaiting to be executed (not shown) on the wireless device 114.

Information Processing System

FIG. 7 is a block diagram illustrating a more detailed view of aninformation processing system 138. It should be noted that although thefollowing discussion is with respect to the information processingsystem 138 comprising the cognitive engine 140 and the dynamic resourceallocator 142, the information processing system 138 is based upon asuitably configured processing system adapted to implement oneembodiment of the present invention. For example, a personal computer,workstation, or the like, may be used. The information processing system138 includes a computer 702. The computer 702 has a CPU processor 704that is connected to a main memory 706, a mass storage interface 708, aman-machine interface 710, and network adapter hardware 716. A systembus 714 interconnects these system components.

The main memory 706 includes the cognitive engine 140, the dynamicresource allocator 142, the application 306, application protocol stack308, policy engine 310, location database 312, and spectrum sensingresults 314 (which can be included in the memory 706 or a separate datastore on the information processing system 138), which have beendiscussed in greater detail above.

Although illustrated as concurrently resident in the main memory 706, itis clear that respective components of the main memory 706 are notrequired to be completely resident in the main memory 706 at all timesor even at the same time. Furthermore, one or more of these componentscan be implemented as hardware. The mass storage interface 708 can storedata on a hard-drive or media such as a CD or DVD. The man-machineinterface 710 allows technicians, administrators, and other users todirectly connect to the information processing system 138 via one ormore terminals 718. The network adapter hardware 716, in one embodiment,is used to provide an interface to the communication network 106, 108.Certain embodiments of the present invention are able to be adapted towork with any data communications links, including present day analogand/or digital techniques or via a future networking mechanism.

Process of Dynamically Allocating Spectrum Sensing Resources

FIG. 8 is an operational flow diagram illustrating process ofdynamically allocating spectrum sensing resources according to oneembodiment of the present invention. The operational flow diagram ofFIG. 8 begins at step 801 and flows directly to step 802. The cognitiveengine 140, at step 804, receives a first input that includes availablesensing session time. A second input, at step 806, is received by thecognitive engine 140 that includes the set of channels to be monitoredduring spectrum sensing. The cognitive engine 140, at step 808, receivesa third input that includes detection constraints associated with one ormore available sensing nodes 112, 114, 116, 118. A fourth input, at step810, is received by the cognitive engine 140 that includes one or morepolicy definitions for mitigating interference experienced by a wirelessdevice 120, 120 in the host network during spectrum sensing.

The cognitive engine 140, at step 812, receives a fifth input thatincludes network statistics for determining a communication cost relatedto performing spectrum sensing with respect to the host network 102. Thedynamic resource allocator 142, at step 814, dynamically allocatesspectrum sensing resources to available sensing nodes 112, 114, 116,118, based on the above inputs. The dynamic resource allocator 142dynamically adjusts the length of a spectrum sensing global period 405and sub-period 402, 404. The dynamic resource allocator 142 allocates anumber of channels within the global 405 and sub-period 402, 404 and anumber of sensing nodes 112, 114, 116, 118 to monitor those channelsduring those periods. The control flow then exits at step 816.

Non-Limiting Examples

Although specific embodiments of the invention have been disclosed,those having ordinary skill in the art will understand that changes canbe made to the specific embodiments without departing from the spiritand scope of the invention. The scope of the invention is not to berestricted, therefore, to the specific embodiments, and it is intendedthat the appended claims cover any and all such applications,modifications, and embodiments within the scope of the presentinvention.

1. A method, with a wireless communication controller, for dynamicallyallocating spectrum sensing resources in an opportunistic spectrumaccess wireless communication system, the method comprising: receiving afirst input comprising available sensing session time for performingspectrum sensing with respect to one or more primary systems; receivinga second input comprising a set of communication channels to bemonitored during spectrum sensing; receiving a third input comprisingdetection constraints associated with a plurality of available sensingnodes in a secondary network for performing the spectrum sensing; anddynamically allocating spectrum sensing resources among a set of theplurality of available sensing nodes based on the first, second, andthird input.
 2. The method of claim 1, wherein dynamically allocatingspectrum sensing resources further comprises: dynamically adjusting alength of at least one of a global spectrum sensing frame within asuper-frame and at least one sub-frame within the global spectrumsensing frame.
 3. The method of claim 2, wherein dynamically adjusting alength of at least one of a global spectrum sensing frame furthercomprises: dynamically determining a suitable length of observation timeto perform spectrum sensing according to a current network throughputrequirement.
 4. The method of claim 2, wherein dynamically allocatingspectrum sensing resources further comprises: allocating at least onecommunication channel in the set of communication channels to bemonitored for spectrum sensing by at least one of the available sensingnodes during a first sub-frame in the global spectrum sensing frame. 5.The method of claim 4, wherein dynamically allocating spectrum sensingresources further comprises: allocating at least one differentcommunication channel in the set of communication channels to bemonitored for spectrum sensing by the at least one of the availablesensing nodes during a second sub-frame in the global spectrum sensingframe.
 6. The method of claim 1, wherein dynamically allocating spectrumsensing resources further comprises: generating a resource allocationtable; and transmitting the resource allocation table to a set of thesensing nodes selected to perform spectrum sensing with respect to theone or more primary systems.
 7. The method of claim 6, wherein theresource allocation table comprises: a plurality of communicationchannels in the set of communication channels that are to be monitoredduring spectrum sensing; a set of sensing nodes in the plurality ofavailable sensing nodes that are to monitor one or more of channels inthe plurality of communication channels during spectrum sensing; and atleast one time period that indicates when each sensing node in the setof sensing nodes is to perform spectrum sensing with respect to at leastone communication channel in the plurality of communication channelsassociated with each sensing node.
 8. The method of claim 1, whereindynamically allocating spectrum sensing resources further comprises:dynamically selecting a number of the available sensing nodes to performthe spectrum sensing with respect to the one or more primary systems. 9.The method of claim 1, further comprising: receiving a fourth inputcomprising one or more policy definitions defining interferencemitigation parameters for mitigating interference between potentialtransmissions of the secondary network on a communication channel in theset of communication channels and a wireless device in the one or moreprimary systems communicating on the communication channel.
 10. Themethod of claim 1, further comprising: receiving a fifth inputcomprising network statistics for determining a communication costrelated to performing cooperative spectrum sensing on a givencommunication channel within the set of communication channels.
 11. Awireless communication controller comprising: a cognitive engine adaptedto receive a first input comprising available spectrum sensing sessiontime for performing spectrum sensing with respect to one or more primarysystems; receive a second input comprising a set of communicationschannels to be monitored in the spectrum sensing session time; receive athird input comprising detection constraints associated with a pluralityof available sensing nodes in a secondary network for performing thespectrum sensing; and a dynamic resource allocator communicativelycoupled to the cognitive engine, the dynamic resource allocator adaptedto: dynamically allocate spectrum sensing resources among a set of theplurality of available sensing nodes based on the first, second, andthird input.
 12. The wireless communication controller of claim 11,wherein the dynamic resource allocator is further adapted to dynamicallyallocate spectrum sensing resources by: dynamically adjusting a lengthof at least one of a global spectrum sensing frame within a super-frameand at least one sub-frame within the global spectrum sensing frame. 13.The wireless communication controller of claim 12, wherein the dynamicresource allocator is further adapted to dynamically allocate spectrumsensing resources by: allocating at least one channel in the set ofchannels to be monitored for spectrum sensing by at least one of theavailable sensing nodes during a first sub-frame in the global spectrumsensing frame.
 14. The wireless communication controller of claim 13,wherein the dynamic resource allocator is further adapted to dynamicallyallocate spectrum sensing resources by: allocating at least onedifferent channel in the set of channels to be monitored for spectrumsensing by the at least one of the available sensing nodes during asecond sub-frame in the global spectrum sensing frame.
 15. The wirelesscommunication controller of claim 11, wherein the dynamic resourceallocator is further adapted to dynamically allocate spectrum sensingresources by: generating a resource allocation table; and transmittingthe resource allocation table to a set of the sensing nodes selected toperform spectrum sensing with respect to the one or more primarysystems.
 16. The wireless communication controller of claim 15, whereinthe resource allocation table comprises: a plurality of communicationchannels in the set of communication channels that are to be monitoredduring spectrum sensing; a set of sensing nodes in the plurality ofavailable sensing nodes that are to monitor one or more of channels inthe plurality of communication channels during spectrum sensing; and atleast one time period that indicates when each sensing node in the setof sensing nodes is to perform spectrum sensing with respect to at leastone communication channel in the plurality of communication channelsassociated with each sensing node.
 17. An information processing systemcomprising: a memory; a processor communicatively coupled to the memory;and a wireless communication controller communicatively coupled to thememory and the processor, wherein the wireless communication controllercomprises: a cognitive engine adapted to receive a first inputcomprising available spectrum sensing session time for performingspectrum sensing with respect to one or more primary systems; receive asecond input comprising a set of communications channels to be monitoredin the spectrum sensing session time; receive a third input comprisingdetection constraints associated with a plurality of available sensingnodes in a secondary network for performing the spectrum sensing; and adynamic resource allocator communicatively coupled to the cognitiveengine, the dynamic resource allocator adapted to: dynamically allocatespectrum sensing resources among a set of the plurality of availablesensing nodes based on the first, second, and third input.
 18. Theinformation processing system of claim 17, wherein the dynamic resourceallocator is further adapted to dynamically allocate spectrum sensingresources by: dynamically adjusting a length of at least one of a globalspectrum sensing frame within a super-frame and at least one sub-framewithin the global spectrum sensing frame.
 19. The information processingsystem of claim 18, wherein the dynamic resource allocator is furtheradapted to dynamically allocate spectrum sensing resources by:allocating at least one channel in the set of channels to be monitoredfor spectrum sensing by at least one of the available sensing nodesduring a first sub-frame in the global spectrum sensing frame.
 20. Theinformation processing system of claim 17, wherein the dynamic resourceallocator is further adapted to dynamically allocate spectrum sensingresources by: generating a resource allocation table, wherein theresource allocation table comprises: a plurality of channels in the setof channels that are to be monitored during spectrum sensing; a set ofsensing nodes in the plurality of available sensing nodes that are tomonitor one or more of the channels in the plurality of channels duringspectrum sensing; and at least one time period that indicates when eachsensing node in the set of sensing nodes is to perform spectrum sensingwith respect to at least one channel in the plurality of channelsassociated with each sensing node; and transmitting the resourceallocation table to a set of the sensing nodes selected to performspectrum sensing with respect to the one or more primary systems.